The disclosure relates to the field of digital image capture, processing, composition analytics and feedback.
As repositories of digital images grow, they use up an ever-increasing amount of the storage capacity of electronic devices. As users of smartphones and other mobile electronic devices use the devices' cameras to capture even the most mundane of images, captured images can quickly fill up most or all of the available memory in the device. This problem is compounded in cloud-based data storage facilities, where users back up entire collections of digital photos, many of which may be very similar to each other.
In addition, users of camera-equipped digital devices seek images of higher quality. Both professional and amateur photographers seek ways to capture images that are aesthetically pleasing. While many digital cameras are equipped with image capture assist technology such as grid overlays that help guide a user when framing a picture, technology is not currently available to process an image in real-time and then guide a user as to what adjustments should be made to acquire an additional image that is more aesthetically pleasing, or to help select a most aesthetically pleasing digital image from a corpus of similar images. In addition, as images are increasingly taken by robotic systems (such as aerial drone-mounted cameras rather than humans), there is an increased need to help such systems capture images that will be considered to be of higher aesthetic quality.
The field of aesthetics primarily deals with the analysis of images in order to establish notions of perceived beauty. Formalism, the study of image beauty with respect to realization and position of depicted forms and colors, is the basis of such analysis. The notion of a pictorial balance has been a central tenant in the formal analysis of images and their beauty. Although there have been many references made to balance and harmony within images throughout the history of the visual arts, only recently have we seen attempts to quantify such balance points using computational methods. The proximity of a rudimentary center of mass calculation to the center of the image does show meaningful correlation to viewer preference.
However, the proximity of a center of mass to the center of the image still only provides a limited way of determining pictorial balance. In addition, these methods do not necessarily help when capturing an image, or when editing/cropping the image after the initial capture.
Web and personal image repositories, which include works of art, are dramatically increasing with the introduction of ever simplified documentation and upload features in personal devices, creating the need for computational algorithms that are able to automatically discern the aesthetically appealing from the unappealing. No current system provides effective real-time feedback for improving image composition.